Technical Field
The present teaching relates to methods, systems and programming for health care. More specifically, the present teaching relates to methods, systems, and programming for medical suggestion search.
Discussion of Technical Background
Users of traditional e-prescription systems have to sort through a large number of possible drugs when they are doing e-prescribing or medication reconciliation. This introduces many additional keystrokes and clicks into the user workflow on a per-patient, per medication level. For example, on a typical patient, users of the traditional e-prescription systems have to make over 20 clicks in order to sort through possible drugs in the systems for e-prescribing or medication reconciliation when the patient leaves from the hospital or clinic. Users ordering laboratory tests and radiology procedures face the similar issues with inhibited workflow and potential for error.
Some e-prescription systems allow users to create favorite drug lists instead of going through all the available drugs in the systems. However, each user of those e-prescription systems has to spend a considerable amount of time on manually creating their own favorite lists and modifying the favorite lists every time new drugs are added into the systems. The initial setup of the favorite lists for a heath care organization, e.g., a hospital, may take up to several months. In addition, mistakes occur during the manual creation of the favorite lists by users and may be multiplied for the lifetime of the users in the traditional e-prescription systems with no practical way to identify and correct them. Many Lab/Radiology systems have limited user favorite abilities as well.